The Semantic Bottleneck: Leveraging Semantic Representations for Non-Invasive Speech Decoding
Paper recorded by Signals 4 on 2026-09-09 in cs.CL. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10
Category: cs.CL · 自然语言处理 · first seen 2026-09-10
Abstract
Non-invasive speech decoding remains constrained by the low signal-to-noise ratio of neural recordings, which makes fine-grained reconstruction of phonemes or individual words difficult. Motivated by neuroscientific evidence that high-level semantic representations are distributed across cortical regions and evolve over slower temporal scales, we hypothesize that semantic content may provide a mor
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Cite this page: The Semantic Bottleneck: Leveraging Semantic Representations for Non-Invasive Speech Decoding: the #84 most recent of 186 cs.CL papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/the-semantic-bottleneck-leveraging-semantic-representations-for-non-invasive-spe.html
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